BUG: pd.array preserve PandasArray

doc/source/whatsnew/v1.4.0.rst

@@ -526,6 +526,7 @@ Sparse
 
 ExtensionArray
 ^^^^^^^^^^^^^^
+- Bug in :func:`array` failing to preserve :class:`PandasArray` (:issue:`43887`)
 - NumPy ufuncs ``np.abs``, ``np.positive``, ``np.negative`` now correctly preserve dtype when called on ExtensionArrays that implement ``__abs__, __pos__, __neg__``, respectively. In particular this is fixed for :class:`TimedeltaArray` (:issue:`43899`)
 -
 

pandas/core/arrays/datetimelike.py

@@ -718,8 +718,9 @@ def _validate_listlike(self, value, allow_object: bool = False):
                     msg = self._validation_error_message(value, True)
                     raise TypeError(msg)
 
-        # Do type inference if necessary up front
+        # Do type inference if necessary up front (after unpacking PandasArray)
         # e.g. we passed PeriodIndex.values and got an ndarray of Periods
+        value = extract_array(value, extract_numpy=True)
         value = pd_array(value)
         value = extract_array(value, extract_numpy=True)
 

pandas/core/construction.py

@@ -297,6 +297,7 @@ def array(
     from pandas.core.arrays import (
         BooleanArray,
         DatetimeArray,
+        ExtensionArray,
         FloatingArray,
         IntegerArray,
         IntervalArray,
@@ -310,7 +311,7 @@ def array(
         msg = f"Cannot pass scalar '{data}' to 'pandas.array'."
         raise ValueError(msg)
 
-    if dtype is None and isinstance(data, (ABCSeries, ABCIndex, ABCExtensionArray)):
+    if dtype is None and isinstance(data, (ABCSeries, ABCIndex, ExtensionArray)):
         # Note: we exclude np.ndarray here, will do type inference on it
         dtype = data.dtype
 

pandas/tests/arrays/test_array.py

@@ -50,6 +50,13 @@
         ),
         # String alias passes through to NumPy
         ([1, 2], "float32", PandasArray(np.array([1, 2], dtype="float32"))),
+        ([1, 2], "int64", PandasArray(np.array([1, 2], dtype=np.int64))),
+        # idempotency with e.g. pd.array(pd.array([1, 2], dtype="int64"))
+        (
+            PandasArray(np.array([1, 2], dtype=np.int32)),
+            None,
+            PandasArray(np.array([1, 2], dtype=np.int32)),
+        ),
         # Period alias
         (
             [pd.Period("2000", "D"), pd.Period("2001", "D")],